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Phase Contrast and Differential Interference Contrast Microscopy

Phase Contrast and Differential Interference Contrast Microscopy

Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...

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Updated: Jul 21, 2025

High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning

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Published on: April 28, 2022

基于深度学习的单次定量相位对比成像,基于深度学习.

Yu-Chun Lin¹, Yuan Luo¹, Ying-Ju Chen¹

¹Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, No. 1, Sec. 1, Jen Ai Rd., Zhongzheng Dist., Taipei City 100, Taiwan.

Biomedical optics express

|July 27, 2023

概括

此摘要是机器生成的。

这项研究引入了一种使用深度学习 (DL) 和彩色编码照明的新型单射量差相对比 (DPC) 成像方法. 这种技术可以通过从单次强度测量生成相位图像来实时监测活细胞.

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Published on: April 28, 2022

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Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

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科学领域:

生物医学光学生物医学光学
定量阶段成像技术定量阶段成像技术
深度学习应用程序

背景情况:

定量差相对比 (DPC) 成像对于相位检索至关重要,但需要多次测量,阻碍实时细胞监测.
现有的方法在活细胞成像应用中面临速度和复杂性的局限性.

研究的目的:

开发一种一次性定量DPC成像方法.
通过深度学习 (DL) 和彩色编码照明,实现实时监控活细胞.
从单次强度测量生成同位素定量相位图像.

主要方法:

训练了一个深度学习模型,从一次性强度测量中生成定量阶段图像.
作为输入,使用了带有辐射不对称图案的彩色编码照明.
一个线性梯度的学生与两个轴测量被用于基准真相重建.
该模型在13个不同的细胞系上进行了训练和验证.

主要成果:

基于DL的相位图像与地面真相图像密切匹配,结构相似度指数超过0.98.
基于DL和地面真相图像之间的相位差异小于13%.
该方法证明了生成和真实相位图像之间的视觉相似性.

结论:

该研究验证了使用深度学习用于一次性定量相位成像的可行性.
这种方法显著提升了实时蜂监控能力.
开发的方法为传统的DPC成像提供了更快,更有效的替代方案.